ArticleJournal of bone metabolism2023
Development and Validation of a New Clinical Diagnostic Screening Model for Osteoporosis in Postmenopausal Women.
Article in Journal of bone metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Performance of clinical prediction models for identifying postmenopausal osteoporosis: a systematic review and meta-analysis.BMC musculoskeletal disorders · 2026Pooled it
- Simple clinical predictors for making directive decisions in osteoporosis screening for women: a cross-sectional study.Journal of orthopaedic surgery and research · 2024Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAge and weight are not only strong predictive parameters for osteoporosis diagnosis but can also be easily acquired from patients. This study aimed to develop and validate a new diagnostic screening model for postmenopausal osteoporosis that uses only 2 parameters, viz., age and weight. The discriminative ability of the model was analyzed and compared with that of the osteoporosis self-assessment tool for Asians (OSTA) index.
methodsThe age-weight diagnostic screening model was developed using a retrospective chart review of postmenopausal women aged ≥50 years who underwent dual energy X-ray absorptiometry at a tertiary hospital from November 2017 to April 2022. Logistic regression analysis was used to derive a diagnostic screening model for osteoporosis.
resultsA total of 533 postmenopausal women were included in the study. According to the highest Youden index value, a probability cut-off value of 0.298 was used in the diagnosis screening model at any site, which yielded a sensitivity of 84.3% and a specificity of 53.8%. For increased sensitivity as a screening tool, a cut-off value of 0.254 was proposed to obtain a sensitivity of 90.2% and a specificity of 42.2%. The area under receiver operating characteristic curves from all screening models were significantly higher than those from the OSTA index model (p<0.05).
conclusionsThis study showed the feasibility of a postmenopausal osteoporosis diagnostic screening model that uses 2 strong predictors for osteoporosis diagnosis: age and weight. This age-weight diagnostic model is a simple, effective option in postmenopausal osteoporosis screening.
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